code: def launch_multitask_example(with_tuning: bool = False):
      """
      Demonstration of an example with running a multitask pipeline.
      Synthetic data is used. Task: predict the category of the substance (column "class") <- classification,
      and then predict the concentration based on the predicted category (column "concentration") <- regression.
  
      :param with_tuning: is tuning required or not
      """
      train_input, test_input = prepare_multitask_data()
      multitask_pipeline = get_multitask_pipeline()
  
      if with_tuning:
          tuner = (
              TunerBuilder(train_input.task)
              .with_tuner(SimultaneousTuner)
              .with_metric(RegressionMetricsEnum.MAE)
              .with_iterations(100)
              .with_timeout(timedelta(minutes=2))
              .build(train_input)
          )
          multitask_pipeline = tuner.tune(multitask_pipeline)
  
      multitask_pipeline.fit(train_input)
      side_pipeline = multitask_pipeline.pipeline_for_side_task(
          task_type=TaskTypesEnum.classification
      )
  
      # Replace the name of main "data source" in preprocessor
      side_pipeline.preprocessor.main_target_source_name = "logit"
      side_output = side_pipeline.predict(
          test_input, output_mode="labels"
      )
      output = multitask_pipeline.predict(test_input)
  
      print(f"Predicted classes: {np.ravel(side_output.predict)}")
      print(f"Predicted concentrations: {np.ravel(output.predict)}")
  
file_path: FEDOT/examples/advanced/multitask_classification_regression.py
imports: from datetime import timedelta
  from typing import Tuple
  import numpy
  import pandas
  from golem.core.tuning.simultaneous import SimultaneousTuner
  from fedot.core.data.data import InputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.metrics_repository import RegressionMetricsEnum
  from fedot.core.repository.tasks import TaskTypesEnum, Task
  from fedot.core.utils import fedot_project_root
label_desc: Use image node_id 3 for calling a global function with example usage: launch_multitask_example(with_tuning) without return types